258 research outputs found

    Hybrid Dy-NFIS & RLS equalization for ZCC code in optical-CDMA over multi-mode optical fiber

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    For long haul coherent optical fiber communication systems, it is significant to precisely monitor the quality of transmission links and optical signals. The channel capacity beyond Shannon limit of Single-mode optical fiber (SMOF) is achieved with the help of Multi-mode optical fiber (MMOF), where the signal is multiplexed in different spatial modes. To increase single-mode transmission capacity and to avoid a foreseen “capacity crunch”, researchers have been motivated to employ MMOF as an alternative. Furthermore, different multiplexing techniques could be applied in MMOF to improve the communication system. One of these techniques is the Optical Code Division Multiple Access (Optical-CDMA), which simplifies and decentralizes network controls to improve spectral efficiency and information security increasing flexibility in bandwidth granularity. This technique also allows synchronous and simultaneous transmission medium to be shared by many users. However, during the propagation of the data over the MMOF based on Optical-CDMA, an inevitable encountered issue is pulse dispersion, nonlinearity and MAI due to mode coupling. Moreover, pulse dispersion, nonlinearity and MAI are significant aspects for the evaluation of the performance of high-speed MMOF communication systems based on Optical-CDMA. This work suggests a hybrid algorithm based on nonlinear algorithm (Dynamic evolving neural fuzzy inference (Dy-NFIS)) and linear algorithm (Recursive least squares (RLS)) equalization for ZCC code in Optical-CDMA over MMOF. Root mean squared error (RMSE), mean squared error (MSE) and Structural Similarity index (SSIM) are used to measure performance results

    Variable-step-size LMS adaptive filter for digital chromatic dispersion compensation in PDM-QPSK coherent transmission system

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    High bit rates optical communication systems pose the challenge of their tolerance to linear and nonlinear fiber impairments. Digital filters in coherent optical receivers can be used to mitigate the chromatic dispersion entirely in the optical transmission system. In this paper, the least mean square adaptive filter has been developed for chromatic equalization in a 112-Gbit/s polarization division multiplexed quadrature phase shift keying coherent optical transmission system established on the VPIphotonics simulation platform. It is found that the chromatic dispersion equalization shows a better performance when a smaller step size is used. However, the smaller step size in least mean square filter will lead to a slower iterative operation to achieve the guaranteed convergence. In order to solve this contradiction, an adaptive filter employing variable-step-size least mean square algorithm is proposed to compensate the chromatic dispersion in the 112-Gbit/s coherent communication system. The variable-step-size least mean square filter could make a compromise and optimization between the chromatic dispersion equalization performance and the algorithm converging speed. Meanwhile, the required tap number and the converged tap weights distribution of the variable-step-size least mean square filter for a certain fiber chromatic dispersion are analyzed and discussed in the investigation of the filter feature

    Advanced DSP Techniques for High-Capacity and Energy-Efficient Optical Fiber Communications

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    The rapid proliferation of the Internet has been driving communication networks closer and closer to their limits, while available bandwidth is disappearing due to an ever-increasing network load. Over the past decade, optical fiber communication technology has increased per fiber data rate from 10 Tb/s to exceeding 10 Pb/s. The major explosion came after the maturity of coherent detection and advanced digital signal processing (DSP). DSP has played a critical role in accommodating channel impairments mitigation, enabling advanced modulation formats for spectral efficiency transmission and realizing flexible bandwidth. This book aims to explore novel, advanced DSP techniques to enable multi-Tb/s/channel optical transmission to address pressing bandwidth and power-efficiency demands. It provides state-of-the-art advances and future perspectives of DSP as well

    Equalização digital para sistemas de transmissão ópticos coerentes

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    This thesis focus on the digital equalization of fiber impairments for coherent optical transmission systems. New efficient and low-complexity equalization and mitigation techniques that counteract fiber nonlinear impairments are proposed and the tradeoff between performance and complexity is numerically assessed and experimentally demonstrated in metro and long-haul 400G superchannels-based transmission systems. Digital backpropagation (DBP) based on low-complexity split-step Fourier method and Volterra series nonlinear equalizers are experimentally assessed in an uniform superchannel system. In contrast with standard DBP methods, these techniques prove to be able to be implemented with larger step-sizes, consequently requiring a reduced number of multiplications, and still achieve a significant reach extension over linear equalization techniques. Moreover, given its structure, the complexity of the proposed Volterra-based DBP approach can be easily adjusted by changing the nonlinear filter dimension according to the system requirements, thus providing a higher flexibility to the nonlinear equalization block. A frequency-hybrid superchannel envisioning near-future flexible networks is then proposed as a way to increase the system bit-rate granularity. The problematic of the power-ratio between superchannel carriers is addressed and optimized for linear and nonlinear operation regimes using three distinct FEC paradigms. Applying a single FEC to the entire superchannel has a simpler implementation and is found to be a more robust approach, tolerating larger uncertainties on the system parameters optimization. We also investigate the performance gain provided by the application of different DBP techniques in frequency-hybrid superchannel systems, and its implications on the optimum power-ratio. It is shown that the application of DBP can be restricted to the carrier transporting the higher cardinality QAM format, since the DBP benefit on the other carriers is negligible, which might bring a substantially complexity reduction of the DBP technique applied to the superchannel.A presente tese foca-se na equalização digital das distorções da fibra para sistemas óticos de transmissão coerente. São propostas novas técnicas eficientes e de baixa complexidade para a equalização e mitigação das distorções não lineares da fibra, e o compromisso entre desempenho e complexidade é testado numericamente e demonstrado experimental em sistemas de transmissão metro e longa distância baseados em supercanais 400G. A propagação digital inversa baseada no método de split-step Fourier e equalizadores não lineares de séries de Volterra de baixa complexidade são testadas experimentalmente num sistema baseado em supercanais uniformes. Ao contrário dos métodos convencionais utilizados, estas técnicas podem ser implementadas utilizando menos interações e ainda extender o alcance do sistema face às técnicas de equalização linear. Para além disso, a complexidade do método baseado em Volterra pode ser facilmente ajustada alterando a dimensão do filtro não linear de acordo com os requisitos do sistema, concedendo assim maior flexibilidade ao bloco de equalização não linear. Tendo em vista as futuras redes flexı́veis, um supercanal hı́brido na frequência é proposto de modo a aumentar a granularidade da taxa de transmissão do sistema. A problemática da relação de potência entre as portadoras do supercanal é abordada e optimizada em regimes de operação linear e não linear utilizando paradigmas diferentes de códigos correctores de erros. A aplicação de um único código corrector de erros à totalidade do supercanal mostra ser a abordagem mais robusta, tolerando maiores incertezas na optimização dos parâmetros do sistema. O ganho de desempenho dado pela aplicação de diferentes técnicas de propagação digital inversa em sistemas de supercanais hı́bridos na frequência é tamém analizado, assim como as suas implicações na relação óptima de potência. Mostra-se que esta pode ser restringida à portadora que transporta o formato de modulação de ordem mais elevada, uma vez que o benefı́cio trazido pelas restantes portadotas é negligenciável, permitindo reduzir significativamente a complexidade do algoritmo aplicado.Programa Doutoral em Telecomunicaçõe

    Machine Learning in Digital Signal Processing for Optical Transmission Systems

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    The future demand for digital information will exceed the capabilities of current optical communication systems, which are approaching their limits due to component and fiber intrinsic non-linear effects. Machine learning methods are promising to find new ways of leverage the available resources and to explore new solutions. Although, some of the machine learning methods such as adaptive non-linear filtering and probabilistic modeling are not novel in the field of telecommunication, enhanced powerful architecture designs together with increasing computing power make it possible to tackle more complex problems today. The methods presented in this work apply machine learning on optical communication systems with two main contributions. First, an unsupervised learning algorithm with embedded additive white Gaussian noise (AWGN) channel and appropriate power constraint is trained end-to-end, learning a geometric constellation shape for lowest bit-error rates over amplified and unamplified links. Second, supervised machine learning methods, especially deep neural networks with and without internal cyclical connections, are investigated to combat linear and non-linear inter-symbol interference (ISI) as well as colored noise effects introduced by the components and the fiber. On high-bandwidth coherent optical transmission setups their performances and complexities are experimentally evaluated and benchmarked against conventional digital signal processing (DSP) approaches. This thesis shows how machine learning can be applied to optical communication systems. In particular, it is demonstrated that machine learning is a viable designing and DSP tool to increase the capabilities of optical communication systems

    Full-Field Detection with Electronic Signal Processing

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    Coherent Optical OFDM Modem Employing Artificial Neural Networks for Dispersion and Nonlinearity Compensation in a Long-Haul Transmission System

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    In order to satisfy the ever increasing demand for the bandwidth requirement in broadband services the optical orthogonal frequency division multiplexing (OOFDM) scheme is being considered as a promising technique for future high-capacity optical networks. The aim of this thesis is to investigate, theoretically, the feasibility of implementing the coherent optical OFDM (CO-OOFDM) technique in long haul transmission networks. For CO-OOFDM and Fast-OFDM systems a set of modulation formats dependent analogue to digital converter (ADC) clipping ratio and the quantization bit have been identified, moreover, CO-OOFDM is more resilient to the chromatic dispersion (CD) when compared to the bandwidth efficient Fast-OFDM scheme. For CO-OOFDM systems numerical simulations are undertaken to investigate the effect of the number of sub-carriers, the cyclic prefix (CP), and ADC associated parameters such as the sampling speed, the clipping ratio, and the quantisation bit on the system performance over single mode fibre (SMF) links for data rates up to 80 Gb/s. The use of a large number of sub-carriers is more effective in combating the fibre CD compared to employing a long CP. Moreover, in the presence of fibre non-linearities identifying the optimum number of sub-carriers is a crucial factor in determining the modem performance. For a range of signal data rates up to 40 Gb/s, a set of data rate and transmission distance-dependent optimum ADC parameters are identified in this work. These parameters give rise to a negligible clipping and quantisation noise, moreover, ADC sampling speed can increase the dispersion tolerance while transmitting over SMF links. In addition, simulation results show that the use of adaptive modulation schemes improves the spectrum usage efficiency, thus resulting in higher tolerance to the CD when compared to the case where identical modulation formats are adopted across all sub-carriers. For a given transmission distance utilizing an artificial neural networks (ANN) equalizer improves the system bit error rate (BER) performance by a factor of 50% and 70%, respectively when considering SMF firstly CD and secondly nonlinear effects with CD. Moreover, for a fixed BER of 10-3 utilizing ANN increases the transmission distance by 1.87 times and 2 times, respectively while considering SMF CD and nonlinear effects. The proposed ANN equalizer performs more efficiently in combating SMF non-linearities than the previously published Kerr nonlinearity electrical compensation technique by a factor of 7
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